This invention relates generally to a method of encoding image data. More particularly, the present invention relates to a method for high efficient data compression of image data which is suitable for image communication, rough image formation of image file retrieval, and the like, at a low bit rate.
Data compression systems for compression of image data with a higher efficiency have been desired in order to reduce the cost of image communication and image data and storage to attain a higher response. Conventional image data compression methods can be classified broadly into a predictive coding method and a transform coding method. The former predicts the brightness value of a given pixel from pixels adjacent thereto in a pixel unit and encodes it in a variable length. However, this method cannot provide compression of less than 1 bit/pixel, in principle. On the other hand, the transform coding method divides an image into sub-blocks having a predetermined size (such as 8.times.8 and 16.times.16), and effects orthogonal transform for this block unit and encoding. However, this method is not free from the problem of a limited compression ratio, either, because redundancy in a greater zone exceeding the block size (as typified by a flat background) cannot be utilized.
Besides the two methods described above, a vector quantization method has been investigated intensively in recent years. This method, too, divides an image into sub-blocks of a predetermined size and performs quantization for each block. For this reason, this method is not devoid of the same problem as that of the transform coding method described above. These compression methods are discussed in "Comparison Of Still Picture Coding Methods", published in Communication Society Technical Paper IE83-106, for example. This reference describes comparative studies on the five kinds of methods, i.e., an adaptive casine transform coding, hierarchal Hadamard transform coding, vector quantitization, DPCM coding and adaptive block coding by obtaining the respective S/N ratios, coding quantities and variable data by simulation using a computer. All of these methods involve the problem of the limited compression ratio described above.